APoc (Alignment of Pockets) is a computational method for large-scale structural comparison of protein pockets. A scoring function, Pocket Similarity Score (PS-score), is derived to measure the level of similarity between pockets. Statistical models are employed to estimate the significance of PS-score based on millions of comparisons of random pockets. Apoc is a general, robust method that may be applied to pockets identified by various approaches, such as ligand-binding sites as observed in experimental complex structures, or predicted pockets identified by a pocket detection method. We curate large benchmark data sets to evaluate the performance of APoc and present interesting examples to demonstrate the usefulness of the method.
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Bioinformatics (2013) 29 (5): 597-604.
APoc: large-scale identification of similar protein pockets.
Gao M, Skolnick J.